Missing Growth from Creative Destruction Philippe Aghion, Antonin Bergeaud Timo Boppart, Peter J. Klenow, Huiyu Li∗ August 2018 Abstract When products exit due to entry of better products from new producers, statistical agencies typically impute inflation from surviving products. This understates growth if creatively-destroyed products improve more than surviving products do. Accordingly, the market share of surviving products should shrink. Using entering and exiting establishments to proxy for creative destruction, we estimate missing growth in U.S. Census data on non-farm businesses from 1983–2013. We find: (i) missing growth is substantial — around half a percentage point per year; but (ii) missing growth did not accelerate much after 2005, and therefore does not explain the sharp slowdown in growth since then. ∗Aghion: College` de France and London School of Economics; Bergeaud: Banque de France; Boppart: IIES, Stockholm University; Klenow: Stanford University; Li: Federal Reserve Bank of San Francisco. We thank Raouf Boucekkine, Pablo Fajgelbaum, Gita Gopinath, Colin Hottman and Stephen Redding for excellent discussions and Victoria De Quadros for superb research assistance. Ufuk Akcigit, Robert Feenstra, Chang-Tai Hsieh, Xavier Jaravel, Chad Jones, Per Krusell, Torsten Persson, Ben Pugsley, John Van Reenen, four referees, and numerous seminar participants provided helpful comments. Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the Federal Reserve System or the U.S. Census Bureau. All results have been reviewed to ensure that no confidential information is disclosed. 1 2 1 Introduction Whereas it is straightforward to compute inflation for an unchanging set of goods and services, it is much harder to separate inflation from quality improvements and variety expansion amidst a changing set of items. In the U.S. Consumer Price Index (CPI), over 3% of items exit the market each month (Bils and Klenow, 2004). In the Producer Price Index (PPI) the figure is over 2% per month (Nakamura and Steinsson, 2008). The Boskin Commission (Boskin et al., 1996) highlighted the challenges of measuring quality improvements when incumbents upgrade their products. It also maintained that the CPI does not fully capture the benefits of brand new varieties. We argue that there exists a subtler, overlooked bias in the case of creative destruction. When the producer of the outgoing item does not produce the incoming item, the standard procedure at statistical offices is to resort to some form of imputation. Imputation inserts the average price growth among a set of surviving products that were not creatively destroyed.1 We think this misses some growth because inflation is likely to be below-average for items subject to creative destruction.2 Creative destruction is believed to be a key source of economic growth. See Aghion and Howitt(1992), Akcigit and Kerr(2018), and Aghion, Akcigit and Howitt(2014). We therefore attempt to quantify the extent of “missing growth”—the difference between actual and measured productivity growth—due to the use of imputation in cases of creative destruction. Our estimates are for the U.S. nonfarm business sector over the past three decades. 1U.S. General Accounting Office(1999) details CPI procedures for dealing with product exit. For the PPI, “If no price from a participating company has been received in a particular month, the change in the price of the associated item will, in general, be estimated by averaging the price changes for the other items within the same cell for which price reports have been received.” (U.S. Bureau of Labor Statistics, 2015, p.10) The BLS makes explicit quality adjustments, such as using hedonics, predominantly for goods that undergo periodic model changes by incumbent producers (Groshen et al., 2017). 2A similar bias due to creative destruction could arise at times of regular rotation of items in the CPI and PPI samples. 3 In the first part of the paper we develop a growth model with (exogenous) innovation to provide explicit expressions for missing growth. In this model, innovation may either create new varieties or replace existing varieties with products of higher quality. The quality improvements can be performed by incumbents on their own products, or by competing incumbents and entrants (creative destruction). The model predicts missing growth due to creative destruction if the statistical office resorts to imputation. In the second part of the paper we estimate the magnitude of missing growth based on our model. We use micro data from the U.S. Census on employment at all private nonfarm businesses to estimate missing growth from 1983–2013. We look at employment shares of continuing (incumbent), entering, and exiting plants. If new plants produce new varieties and carry out creative destruction, then the inroads they make in incumbents’ market share should signal their contribution to growth. Our findings can be summarized as follows. First, missing growth from imputation is substantial: roughly one-half a percentage point per year, or around one-third of measured productivity growth. Second, we find only a modest acceleration of missing growth since 2005, an order of magnitude smaller than needed to explain the slowdown in measured growth. Example: The following numerical example illustrates how imputation can miss growth. Suppose that: (i) 80% of products in the economy experience no innovation in a given period and are subject to a 4% inflation rate; (ii) 10% of products experience quality improvement without creative destruction, with their quality-adjusted prices falling 6% (i.e., an inflation rate of -6%); and (iii) 10% of products experience quality improvement due to creative destruction, with their quality-adjusted prices also falling by 6%. The true inflation rate in this economy is then 2%. Suppose further that nominal output grows at 4%, so that true productivity growth is 2% after subtracting the 2% true inflation rate. What happens if the statistical office resorts to imputation in cases of 4 creative destruction? Then it will not correctly decompose growth in nominal output into its inflation and real growth components. Imputation means that the statistical office will ignore the goods subject to creative destruction when computing the inflation rate for the whole economy, and only consider the products that were not subject to innovation plus the products for which innovation did not involve creative destruction. Thus the statistical office will take the average inflation rate for the whole economy to be equal to 8 1 · 4% + · (−6%) = 2:9%: 9 9 Presuming it correctly evaluates the growth in nominal GDP to be 4%, the statistical office will (incorrectly) infer that the growth rate of real output is 4% − 2:9% = 1:1%: This in turn implies “missing growth” in productivity amounting to 2% − 1:1% = 0:9%: This ends our example, which hopefully clarifies the main mechanism by which imputation can miss growth from creative destruction.3 Our paper touches on the recent literature about secular stagnation and growth measurement. Gordon(2012) argues that innovation has run into diminishing returns, inexorably slowing TFP growth.4 Syverson(2016) and Byrne, Fernald and Reinsdorf(2016) conclude that understatement of growth in the ICT sector cannot account for the productivity slowdown since 2005. In contrast to these studies, we look at missing growth for the whole economy, not just from the ICT sector. 3This example is stylized. In practice, imputation by the BLS is carried out within the items category or category-region. See the U.S. General Accounting Office(1999). 4Related studies include Jones(1995), Kortum(1997), and Bloom et al.(2017). 5 More closely related to our analysis are Feenstra(1994), Bils and Klenow (2001), Bils(2009), Broda and Weinstein(2010), Erickson and Pakes(2011), Byrne, Oliner and Sichel(2015), and Redding and Weinstein(2016). 5 We make two contributions relative to these important papers. First, we compute missing growth for the entire private nonfarm sector from 1983–2013.6 Second, we focus on a neglected source of missing growth, namely imputation in the event of creative destruction. The missing growth we identify is likely to be exacerbated when there is error in measuring quality improvements by incumbents on their own products.7 The rest of the paper is organized as follows. In Section2 we lay out an environment relating missing growth to creative destruction. In Section3 we estimate missing growth using U.S. Census data on plant market shares. Section4 compares our estimates to those in three existing studies. Section5 concludes. 2 A model of missing growth In this section we relate our measure of missing growth to Feenstra(1994). We modify his approach to focus on bias from new producers of a given product 5Feenstra(1994) corrects for biases in the U.S. import price indices of six manufacturing goods, in particular due to an expanding set of available product varieties. Bils and Klenow (2001) use the U.S. Consumer Expenditure surveys to estimate “quality Engel curves” and assess the unmeasured quality growth of 66 durable goods which account for 12% of consumer spending. Bils(2009) uses CPI micro data to decompose the observed price increases of durable goods into quality changes and true inflation. Broda and Weinstein(2010) look at missing growth from entry and exit of products in the nondurable retail sector, using an AC Nielsen database. Byrne, Oliner and Sichel(2015) look at missing growth in the semiconductor sector. 6Broda and Weinstein(2010) used AC Nielsen data from 1994 and 1999–2003. This database is heavily weighted toward nondurables, particularly food. Bils and Klenow(2004) report a product exit rate of about 2.4% per month for nondurables (1.2% a month for food) versus about 6.2% per month for durable goods. Hence, it is important to analyze missing growth across many sectors of the economy, including durables.